3 papers
cs.CV2024
Robustly overfitting latents for flexible neural image compression
Yura Perugachi-Diaz, Arwin Gansekoele, Sandjai Bhulai
Neural image compression has made a great deal of progress. State-of-the-art models are based on variational autoencoders and are outperforming classical models. Neural compression…
stat.ML2021
Invertible DenseNets with Concatenated LipSwish
Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
We introduce Invertible Dense Networks (i-DenseNets), a more parameter efficient extension of Residual Flows. The method relies on an analysis of the Lipschitz continuity of the co…
cs.LG2020
Invertible DenseNets
Yura Perugachi-Diaz, Jakub M. Tomczak, Sandjai Bhulai
We introduce Invertible Dense Networks (i-DenseNets), a more parameter efficient alternative to Residual Flows. The method relies on an analysis of the Lipschitz continuity of the…